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923 lines
29 KiB
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923 lines
29 KiB
Plaintext
================================
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PostgreSQL specific model fields
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================================
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All of these fields are available from the ``django.contrib.postgres.fields``
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module.
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.. currentmodule:: django.contrib.postgres.fields
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Indexing these fields
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=====================
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:class:`~django.db.models.Index` and :attr:`.Field.db_index` both create a
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B-tree index, which isn't particularly helpful when querying complex data types.
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Indexes such as :class:`~django.contrib.postgres.indexes.GinIndex` and
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:class:`~django.contrib.postgres.indexes.GistIndex` are better suited, though
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the index choice is dependent on the queries that you're using. Generally, GiST
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may be a good choice for the :ref:`range fields <range-fields>` and
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:class:`HStoreField`, and GIN may be helpful for :class:`ArrayField`.
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``ArrayField``
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==============
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.. class:: ArrayField(base_field, size=None, **options)
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A field for storing lists of data. Most field types can be used, and you
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pass another field instance as the :attr:`base_field
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<ArrayField.base_field>`. You may also specify a :attr:`size
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<ArrayField.size>`. ``ArrayField`` can be nested to store multi-dimensional
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arrays.
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If you give the field a :attr:`~django.db.models.Field.default`, ensure
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it's a callable such as ``list`` (for an empty default) or a callable that
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returns a list (such as a function). Incorrectly using ``default=[]``
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creates a mutable default that is shared between all instances of
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``ArrayField``.
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.. attribute:: base_field
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This is a required argument.
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Specifies the underlying data type and behavior for the array. It
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should be an instance of a subclass of
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:class:`~django.db.models.Field`. For example, it could be an
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:class:`~django.db.models.IntegerField` or a
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:class:`~django.db.models.CharField`. Most field types are permitted,
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with the exception of those handling relational data
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(:class:`~django.db.models.ForeignKey`,
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:class:`~django.db.models.OneToOneField` and
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:class:`~django.db.models.ManyToManyField`) and file fields (
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:class:`~django.db.models.FileField` and
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:class:`~django.db.models.ImageField`).
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It is possible to nest array fields - you can specify an instance of
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``ArrayField`` as the ``base_field``. For example::
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from django.contrib.postgres.fields import ArrayField
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from django.db import models
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class ChessBoard(models.Model):
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board = ArrayField(
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ArrayField(
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models.CharField(max_length=10, blank=True),
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size=8,
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),
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size=8,
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)
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Transformation of values between the database and the model, validation
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of data and configuration, and serialization are all delegated to the
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underlying base field.
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.. attribute:: size
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This is an optional argument.
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If passed, the array will have a maximum size as specified. This will
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be passed to the database, although PostgreSQL at present does not
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enforce the restriction.
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.. note::
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When nesting ``ArrayField``, whether you use the ``size`` parameter or not,
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PostgreSQL requires that the arrays are rectangular::
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from django.contrib.postgres.fields import ArrayField
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from django.db import models
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class Board(models.Model):
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pieces = ArrayField(ArrayField(models.IntegerField()))
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# Valid
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Board(
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pieces=[
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[2, 3],
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[2, 1],
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]
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)
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# Not valid
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Board(
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pieces=[
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[2, 3],
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[2],
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]
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)
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If irregular shapes are required, then the underlying field should be made
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nullable and the values padded with ``None``.
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Querying ``ArrayField``
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-----------------------
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There are a number of custom lookups and transforms for :class:`ArrayField`.
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We will use the following example model::
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from django.contrib.postgres.fields import ArrayField
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from django.db import models
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class Post(models.Model):
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name = models.CharField(max_length=200)
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tags = ArrayField(models.CharField(max_length=200), blank=True)
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def __str__(self):
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return self.name
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.. fieldlookup:: arrayfield.contains
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``contains``
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~~~~~~~~~~~~
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The :lookup:`contains` lookup is overridden on :class:`ArrayField`. The
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returned objects will be those where the values passed are a subset of the
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data. It uses the SQL operator ``@>``. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts"])
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>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])
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>>> Post.objects.filter(tags__contains=["thoughts"])
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<QuerySet [<Post: First post>, <Post: Second post>]>
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>>> Post.objects.filter(tags__contains=["django"])
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<QuerySet [<Post: First post>, <Post: Third post>]>
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>>> Post.objects.filter(tags__contains=["django", "thoughts"])
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<QuerySet [<Post: First post>]>
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.. fieldlookup:: arrayfield.contained_by
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``contained_by``
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~~~~~~~~~~~~~~~~
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This is the inverse of the :lookup:`contains <arrayfield.contains>` lookup -
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the objects returned will be those where the data is a subset of the values
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passed. It uses the SQL operator ``<@``. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts"])
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>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])
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>>> Post.objects.filter(tags__contained_by=["thoughts", "django"])
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<QuerySet [<Post: First post>, <Post: Second post>]>
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>>> Post.objects.filter(tags__contained_by=["thoughts", "django", "tutorial"])
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<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>
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.. fieldlookup:: arrayfield.overlap
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``overlap``
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~~~~~~~~~~~
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Returns objects where the data shares any results with the values passed. Uses
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the SQL operator ``&&``. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts", "tutorial"])
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>>> Post.objects.create(name="Third post", tags=["tutorial", "django"])
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>>> Post.objects.filter(tags__overlap=["thoughts"])
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<QuerySet [<Post: First post>, <Post: Second post>]>
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>>> Post.objects.filter(tags__overlap=["thoughts", "tutorial"])
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<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>
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>>> Post.objects.filter(tags__overlap=Post.objects.values_list("tags"))
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<QuerySet [<Post: First post>, <Post: Second post>, <Post: Third post>]>
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.. fieldlookup:: arrayfield.len
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``len``
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~~~~~~~
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Returns the length of the array. The lookups available afterward are those
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available for :class:`~django.db.models.IntegerField`. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts"])
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>>> Post.objects.filter(tags__len=1)
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<QuerySet [<Post: Second post>]>
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.. fieldlookup:: arrayfield.index
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Index transforms
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~~~~~~~~~~~~~~~~
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Index transforms index into the array. Any non-negative integer can be used.
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There are no errors if it exceeds the :attr:`size <ArrayField.size>` of the
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array. The lookups available after the transform are those from the
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:attr:`base_field <ArrayField.base_field>`. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts"])
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>>> Post.objects.filter(tags__0="thoughts")
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<QuerySet [<Post: First post>, <Post: Second post>]>
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>>> Post.objects.filter(tags__1__iexact="Django")
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<QuerySet [<Post: First post>]>
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>>> Post.objects.filter(tags__276="javascript")
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<QuerySet []>
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.. note::
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PostgreSQL uses 1-based indexing for array fields when writing raw SQL.
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However these indexes and those used in :lookup:`slices <arrayfield.slice>`
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use 0-based indexing to be consistent with Python.
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.. fieldlookup:: arrayfield.slice
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Slice transforms
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~~~~~~~~~~~~~~~~
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Slice transforms take a slice of the array. Any two non-negative integers can
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be used, separated by a single underscore. The lookups available after the
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transform do not change. For example:
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.. code-block:: pycon
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>>> Post.objects.create(name="First post", tags=["thoughts", "django"])
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>>> Post.objects.create(name="Second post", tags=["thoughts"])
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>>> Post.objects.create(name="Third post", tags=["django", "python", "thoughts"])
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>>> Post.objects.filter(tags__0_1=["thoughts"])
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<QuerySet [<Post: First post>, <Post: Second post>]>
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>>> Post.objects.filter(tags__0_2__contains=["thoughts"])
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<QuerySet [<Post: First post>, <Post: Second post>]>
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.. note::
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PostgreSQL uses 1-based indexing for array fields when writing raw SQL.
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However these slices and those used in :lookup:`indexes <arrayfield.index>`
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use 0-based indexing to be consistent with Python.
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.. admonition:: Multidimensional arrays with indexes and slices
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PostgreSQL has some rather esoteric behavior when using indexes and slices
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on multidimensional arrays. It will always work to use indexes to reach
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down to the final underlying data, but most other slices behave strangely
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at the database level and cannot be supported in a logical, consistent
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fashion by Django.
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``HStoreField``
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===============
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.. class:: HStoreField(**options)
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A field for storing key-value pairs. The Python data type used is a
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``dict``. Keys must be strings, and values may be either strings or nulls
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(``None`` in Python).
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To use this field, you'll need to:
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#. Add ``'django.contrib.postgres'`` in your :setting:`INSTALLED_APPS`.
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#. :ref:`Set up the hstore extension <create-postgresql-extensions>` in
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PostgreSQL.
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You'll see an error like ``can't adapt type 'dict'`` if you skip the first
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step, or ``type "hstore" does not exist`` if you skip the second.
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.. note::
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On occasions it may be useful to require or restrict the keys which are
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valid for a given field. This can be done using the
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:class:`~django.contrib.postgres.validators.KeysValidator`.
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Querying ``HStoreField``
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------------------------
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In addition to the ability to query by key, there are a number of custom
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lookups available for ``HStoreField``.
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We will use the following example model::
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from django.contrib.postgres.fields import HStoreField
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from django.db import models
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class Dog(models.Model):
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name = models.CharField(max_length=200)
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data = HStoreField()
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def __str__(self):
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return self.name
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.. fieldlookup:: hstorefield.key
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Key lookups
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~~~~~~~~~~~
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To query based on a given key, you can use that key as the lookup name:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie"})
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>>> Dog.objects.filter(data__breed="collie")
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<QuerySet [<Dog: Meg>]>
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You can chain other lookups after key lookups:
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.. code-block:: pycon
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>>> Dog.objects.filter(data__breed__contains="l")
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<QuerySet [<Dog: Rufus>, <Dog: Meg>]>
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or use ``F()`` expressions to annotate a key value. For example:
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.. code-block:: pycon
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>>> from django.db.models import F
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>>> rufus = Dog.objects.annotate(breed=F("data__breed"))[0]
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>>> rufus.breed
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'labrador'
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If the key you wish to query by clashes with the name of another lookup, you
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need to use the :lookup:`hstorefield.contains` lookup instead.
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.. note::
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Key transforms can also be chained with: :lookup:`contains`,
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:lookup:`icontains`, :lookup:`endswith`, :lookup:`iendswith`,
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:lookup:`iexact`, :lookup:`regex`, :lookup:`iregex`, :lookup:`startswith`,
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and :lookup:`istartswith` lookups.
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.. warning::
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Since any string could be a key in a hstore value, any lookup other than
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those listed below will be interpreted as a key lookup. No errors are
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raised. Be extra careful for typing mistakes, and always check your queries
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work as you intend.
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.. fieldlookup:: hstorefield.contains
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``contains``
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~~~~~~~~~~~~
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The :lookup:`contains` lookup is overridden on
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:class:`~django.contrib.postgres.fields.HStoreField`. The returned objects are
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those where the given ``dict`` of key-value pairs are all contained in the
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field. It uses the SQL operator ``@>``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.create(name="Fred", data={})
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>>> Dog.objects.filter(data__contains={"owner": "Bob"})
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<QuerySet [<Dog: Rufus>, <Dog: Meg>]>
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>>> Dog.objects.filter(data__contains={"breed": "collie"})
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<QuerySet [<Dog: Meg>]>
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.. fieldlookup:: hstorefield.contained_by
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``contained_by``
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~~~~~~~~~~~~~~~~
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This is the inverse of the :lookup:`contains <hstorefield.contains>` lookup -
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the objects returned will be those where the key-value pairs on the object are
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a subset of those in the value passed. It uses the SQL operator ``<@``. For
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example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador", "owner": "Bob"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.create(name="Fred", data={})
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>>> Dog.objects.filter(data__contained_by={"breed": "collie", "owner": "Bob"})
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<QuerySet [<Dog: Meg>, <Dog: Fred>]>
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>>> Dog.objects.filter(data__contained_by={"breed": "collie"})
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<QuerySet [<Dog: Fred>]>
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.. fieldlookup:: hstorefield.has_key
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``has_key``
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~~~~~~~~~~~
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Returns objects where the given key is in the data. Uses the SQL operator
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``?``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.filter(data__has_key="owner")
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<QuerySet [<Dog: Meg>]>
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.. fieldlookup:: hstorefield.has_any_keys
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``has_any_keys``
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~~~~~~~~~~~~~~~~
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Returns objects where any of the given keys are in the data. Uses the SQL
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operator ``?|``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
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>>> Dog.objects.create(name="Meg", data={"owner": "Bob"})
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>>> Dog.objects.create(name="Fred", data={})
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>>> Dog.objects.filter(data__has_any_keys=["owner", "breed"])
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<QuerySet [<Dog: Rufus>, <Dog: Meg>]>
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.. fieldlookup:: hstorefield.has_keys
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``has_keys``
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~~~~~~~~~~~~
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Returns objects where all of the given keys are in the data. Uses the SQL operator
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``?&``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.filter(data__has_keys=["breed", "owner"])
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<QuerySet [<Dog: Meg>]>
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.. fieldlookup:: hstorefield.keys
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``keys``
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~~~~~~~~
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Returns objects where the array of keys is the given value. Note that the order
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is not guaranteed to be reliable, so this transform is mainly useful for using
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in conjunction with lookups on
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:class:`~django.contrib.postgres.fields.ArrayField`. Uses the SQL function
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``akeys()``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"toy": "bone"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.filter(data__keys__overlap=["breed", "toy"])
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<QuerySet [<Dog: Rufus>, <Dog: Meg>]>
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.. fieldlookup:: hstorefield.values
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``values``
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~~~~~~~~~~
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Returns objects where the array of values is the given value. Note that the
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order is not guaranteed to be reliable, so this transform is mainly useful for
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using in conjunction with lookups on
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:class:`~django.contrib.postgres.fields.ArrayField`. Uses the SQL function
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``avals()``. For example:
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.. code-block:: pycon
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>>> Dog.objects.create(name="Rufus", data={"breed": "labrador"})
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>>> Dog.objects.create(name="Meg", data={"breed": "collie", "owner": "Bob"})
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>>> Dog.objects.filter(data__values__contains=["collie"])
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<QuerySet [<Dog: Meg>]>
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.. _range-fields:
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Range Fields
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============
|
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There are five range field types, corresponding to the built-in range types in
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PostgreSQL. These fields are used to store a range of values; for example the
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start and end timestamps of an event, or the range of ages an activity is
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suitable for.
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All of the range fields translate to :ref:`psycopg Range objects
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<psycopg:adapt-range>` in Python, but also accept tuples as input if no bounds
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information is necessary. The default is lower bound included, upper bound
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excluded, that is ``[)`` (see the PostgreSQL documentation for details about
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`different bounds`_). The default bounds can be changed for non-discrete range
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fields (:class:`.DateTimeRangeField` and :class:`.DecimalRangeField`) by using
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the ``default_bounds`` argument.
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|
|
``IntegerRangeField``
|
|
---------------------
|
|
|
|
.. class:: IntegerRangeField(**options)
|
|
|
|
Stores a range of integers. Based on an
|
|
:class:`~django.db.models.IntegerField`. Represented by an ``int4range`` in
|
|
the database and a
|
|
``django.db.backends.postgresql.psycopg_any.NumericRange`` in Python.
|
|
|
|
Regardless of the bounds specified when saving the data, PostgreSQL always
|
|
returns a range in a canonical form that includes the lower bound and
|
|
excludes the upper bound, that is ``[)``.
|
|
|
|
``BigIntegerRangeField``
|
|
------------------------
|
|
|
|
.. class:: BigIntegerRangeField(**options)
|
|
|
|
Stores a range of large integers. Based on a
|
|
:class:`~django.db.models.BigIntegerField`. Represented by an ``int8range``
|
|
in the database and a
|
|
``django.db.backends.postgresql.psycopg_any.NumericRange`` in Python.
|
|
|
|
Regardless of the bounds specified when saving the data, PostgreSQL always
|
|
returns a range in a canonical form that includes the lower bound and
|
|
excludes the upper bound, that is ``[)``.
|
|
|
|
``DecimalRangeField``
|
|
---------------------
|
|
|
|
.. class:: DecimalRangeField(default_bounds='[)', **options)
|
|
|
|
Stores a range of floating point values. Based on a
|
|
:class:`~django.db.models.DecimalField`. Represented by a ``numrange`` in
|
|
the database and a
|
|
``django.db.backends.postgresql.psycopg_any.NumericRange`` in Python.
|
|
|
|
.. attribute:: DecimalRangeField.default_bounds
|
|
|
|
Optional. The value of ``bounds`` for list and tuple inputs. The
|
|
default is lower bound included, upper bound excluded, that is ``[)``
|
|
(see the PostgreSQL documentation for details about
|
|
`different bounds`_). ``default_bounds`` is not used for
|
|
``django.db.backends.postgresql.psycopg_any.NumericRange`` inputs.
|
|
|
|
``DateTimeRangeField``
|
|
----------------------
|
|
|
|
.. class:: DateTimeRangeField(default_bounds='[)', **options)
|
|
|
|
Stores a range of timestamps. Based on a
|
|
:class:`~django.db.models.DateTimeField`. Represented by a ``tstzrange`` in
|
|
the database and a
|
|
``django.db.backends.postgresql.psycopg_any.DateTimeTZRange`` in Python.
|
|
|
|
.. attribute:: DateTimeRangeField.default_bounds
|
|
|
|
Optional. The value of ``bounds`` for list and tuple inputs. The
|
|
default is lower bound included, upper bound excluded, that is ``[)``
|
|
(see the PostgreSQL documentation for details about
|
|
`different bounds`_). ``default_bounds`` is not used for
|
|
``django.db.backends.postgresql.psycopg_any.DateTimeTZRange`` inputs.
|
|
|
|
``DateRangeField``
|
|
------------------
|
|
|
|
.. class:: DateRangeField(**options)
|
|
|
|
Stores a range of dates. Based on a
|
|
:class:`~django.db.models.DateField`. Represented by a ``daterange`` in the
|
|
database and a ``django.db.backends.postgresql.psycopg_any.DateRange`` in
|
|
Python.
|
|
|
|
Regardless of the bounds specified when saving the data, PostgreSQL always
|
|
returns a range in a canonical form that includes the lower bound and
|
|
excludes the upper bound, that is ``[)``.
|
|
|
|
Querying Range Fields
|
|
---------------------
|
|
|
|
There are a number of custom lookups and transforms for range fields. They are
|
|
available on all the above fields, but we will use the following example
|
|
model::
|
|
|
|
from django.contrib.postgres.fields import IntegerRangeField
|
|
from django.db import models
|
|
|
|
|
|
class Event(models.Model):
|
|
name = models.CharField(max_length=200)
|
|
ages = IntegerRangeField()
|
|
start = models.DateTimeField()
|
|
|
|
def __str__(self):
|
|
return self.name
|
|
|
|
We will also use the following example objects:
|
|
|
|
.. code-block:: pycon
|
|
|
|
>>> import datetime
|
|
>>> from django.utils import timezone
|
|
>>> now = timezone.now()
|
|
>>> Event.objects.create(name="Soft play", ages=(0, 10), start=now)
|
|
>>> Event.objects.create(
|
|
... name="Pub trip", ages=(21, None), start=now - datetime.timedelta(days=1)
|
|
... )
|
|
|
|
and ``NumericRange``:
|
|
|
|
>>> from django.db.backends.postgresql.psycopg_any import NumericRange
|
|
|
|
Containment functions
|
|
~~~~~~~~~~~~~~~~~~~~~
|
|
|
|
As with other PostgreSQL fields, there are three standard containment
|
|
operators: ``contains``, ``contained_by`` and ``overlap``, using the SQL
|
|
operators ``@>``, ``<@``, and ``&&`` respectively.
|
|
|
|
.. fieldlookup:: rangefield.contains
|
|
|
|
``contains``
|
|
^^^^^^^^^^^^
|
|
|
|
>>> Event.objects.filter(ages__contains=NumericRange(4, 5))
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
.. fieldlookup:: rangefield.contained_by
|
|
|
|
``contained_by``
|
|
^^^^^^^^^^^^^^^^
|
|
|
|
>>> Event.objects.filter(ages__contained_by=NumericRange(0, 15))
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
The ``contained_by`` lookup is also available on the non-range field types:
|
|
:class:`~django.db.models.SmallAutoField`,
|
|
:class:`~django.db.models.AutoField`, :class:`~django.db.models.BigAutoField`,
|
|
:class:`~django.db.models.SmallIntegerField`,
|
|
:class:`~django.db.models.IntegerField`,
|
|
:class:`~django.db.models.BigIntegerField`,
|
|
:class:`~django.db.models.DecimalField`, :class:`~django.db.models.FloatField`,
|
|
:class:`~django.db.models.DateField`, and
|
|
:class:`~django.db.models.DateTimeField`. For example:
|
|
|
|
.. code-block:: pycon
|
|
|
|
>>> from django.db.backends.postgresql.psycopg_any import DateTimeTZRange
|
|
>>> Event.objects.filter(
|
|
... start__contained_by=DateTimeTZRange(
|
|
... timezone.now() - datetime.timedelta(hours=1),
|
|
... timezone.now() + datetime.timedelta(hours=1),
|
|
... ),
|
|
... )
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
.. fieldlookup:: rangefield.overlap
|
|
|
|
``overlap``
|
|
^^^^^^^^^^^
|
|
|
|
>>> Event.objects.filter(ages__overlap=NumericRange(8, 12))
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
Comparison functions
|
|
~~~~~~~~~~~~~~~~~~~~
|
|
|
|
Range fields support the standard lookups: :lookup:`lt`, :lookup:`gt`,
|
|
:lookup:`lte` and :lookup:`gte`. These are not particularly helpful - they
|
|
compare the lower bounds first and then the upper bounds only if necessary.
|
|
This is also the strategy used to order by a range field. It is better to use
|
|
the specific range comparison operators.
|
|
|
|
.. fieldlookup:: rangefield.fully_lt
|
|
|
|
``fully_lt``
|
|
^^^^^^^^^^^^
|
|
|
|
The returned ranges are strictly less than the passed range. In other words,
|
|
all the points in the returned range are less than all those in the passed
|
|
range.
|
|
|
|
>>> Event.objects.filter(ages__fully_lt=NumericRange(11, 15))
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
.. fieldlookup:: rangefield.fully_gt
|
|
|
|
``fully_gt``
|
|
^^^^^^^^^^^^
|
|
|
|
The returned ranges are strictly greater than the passed range. In other words,
|
|
the all the points in the returned range are greater than all those in the
|
|
passed range.
|
|
|
|
>>> Event.objects.filter(ages__fully_gt=NumericRange(11, 15))
|
|
<QuerySet [<Event: Pub trip>]>
|
|
|
|
.. fieldlookup:: rangefield.not_lt
|
|
|
|
``not_lt``
|
|
^^^^^^^^^^
|
|
|
|
The returned ranges do not contain any points less than the passed range, that
|
|
is the lower bound of the returned range is at least the lower bound of the
|
|
passed range.
|
|
|
|
>>> Event.objects.filter(ages__not_lt=NumericRange(0, 15))
|
|
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>
|
|
|
|
.. fieldlookup:: rangefield.not_gt
|
|
|
|
``not_gt``
|
|
^^^^^^^^^^
|
|
|
|
The returned ranges do not contain any points greater than the passed range, that
|
|
is the upper bound of the returned range is at most the upper bound of the
|
|
passed range.
|
|
|
|
>>> Event.objects.filter(ages__not_gt=NumericRange(3, 10))
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
.. fieldlookup:: rangefield.adjacent_to
|
|
|
|
``adjacent_to``
|
|
^^^^^^^^^^^^^^^
|
|
|
|
The returned ranges share a bound with the passed range.
|
|
|
|
>>> Event.objects.filter(ages__adjacent_to=NumericRange(10, 21))
|
|
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>
|
|
|
|
Querying using the bounds
|
|
~~~~~~~~~~~~~~~~~~~~~~~~~
|
|
|
|
Range fields support several extra lookups.
|
|
|
|
.. fieldlookup:: rangefield.startswith
|
|
|
|
``startswith``
|
|
^^^^^^^^^^^^^^
|
|
|
|
Returned objects have the given lower bound. Can be chained to valid lookups
|
|
for the base field.
|
|
|
|
>>> Event.objects.filter(ages__startswith=21)
|
|
<QuerySet [<Event: Pub trip>]>
|
|
|
|
.. fieldlookup:: rangefield.endswith
|
|
|
|
``endswith``
|
|
^^^^^^^^^^^^
|
|
|
|
Returned objects have the given upper bound. Can be chained to valid lookups
|
|
for the base field.
|
|
|
|
>>> Event.objects.filter(ages__endswith=10)
|
|
<QuerySet [<Event: Soft play>]>
|
|
|
|
.. fieldlookup:: rangefield.isempty
|
|
|
|
``isempty``
|
|
^^^^^^^^^^^
|
|
|
|
Returned objects are empty ranges. Can be chained to valid lookups for a
|
|
:class:`~django.db.models.BooleanField`.
|
|
|
|
>>> Event.objects.filter(ages__isempty=True)
|
|
<QuerySet []>
|
|
|
|
.. fieldlookup:: rangefield.lower_inc
|
|
|
|
``lower_inc``
|
|
^^^^^^^^^^^^^
|
|
|
|
Returns objects that have inclusive or exclusive lower bounds, depending on the
|
|
boolean value passed. Can be chained to valid lookups for a
|
|
:class:`~django.db.models.BooleanField`.
|
|
|
|
>>> Event.objects.filter(ages__lower_inc=True)
|
|
<QuerySet [<Event: Soft play>, <Event: Pub trip>]>
|
|
|
|
.. fieldlookup:: rangefield.lower_inf
|
|
|
|
``lower_inf``
|
|
^^^^^^^^^^^^^
|
|
|
|
Returns objects that have unbounded (infinite) or bounded lower bound,
|
|
depending on the boolean value passed. Can be chained to valid lookups for a
|
|
:class:`~django.db.models.BooleanField`.
|
|
|
|
>>> Event.objects.filter(ages__lower_inf=True)
|
|
<QuerySet []>
|
|
|
|
.. fieldlookup:: rangefield.upper_inc
|
|
|
|
``upper_inc``
|
|
^^^^^^^^^^^^^
|
|
|
|
Returns objects that have inclusive or exclusive upper bounds, depending on the
|
|
boolean value passed. Can be chained to valid lookups for a
|
|
:class:`~django.db.models.BooleanField`.
|
|
|
|
>>> Event.objects.filter(ages__upper_inc=True)
|
|
<QuerySet []>
|
|
|
|
.. fieldlookup:: rangefield.upper_inf
|
|
|
|
``upper_inf``
|
|
^^^^^^^^^^^^^
|
|
|
|
Returns objects that have unbounded (infinite) or bounded upper bound,
|
|
depending on the boolean value passed. Can be chained to valid lookups for a
|
|
:class:`~django.db.models.BooleanField`.
|
|
|
|
>>> Event.objects.filter(ages__upper_inf=True)
|
|
<QuerySet [<Event: Pub trip>]>
|
|
|
|
Defining your own range types
|
|
-----------------------------
|
|
|
|
PostgreSQL allows the definition of custom range types. Django's model and form
|
|
field implementations use base classes below, and ``psycopg`` provides a
|
|
:func:`~psycopg:psycopg.types.range.register_range` to allow use of custom
|
|
range types.
|
|
|
|
.. class:: RangeField(**options)
|
|
|
|
Base class for model range fields.
|
|
|
|
.. attribute:: base_field
|
|
|
|
The model field class to use.
|
|
|
|
.. attribute:: range_type
|
|
|
|
The range type to use.
|
|
|
|
.. attribute:: form_field
|
|
|
|
The form field class to use. Should be a subclass of
|
|
:class:`django.contrib.postgres.forms.BaseRangeField`.
|
|
|
|
.. class:: django.contrib.postgres.forms.BaseRangeField
|
|
|
|
Base class for form range fields.
|
|
|
|
.. attribute:: base_field
|
|
|
|
The form field to use.
|
|
|
|
.. attribute:: range_type
|
|
|
|
The range type to use.
|
|
|
|
Range operators
|
|
---------------
|
|
|
|
.. class:: RangeOperators
|
|
|
|
PostgreSQL provides a set of SQL operators that can be used together with the
|
|
range data types (see `the PostgreSQL documentation for the full details of
|
|
range operators <https://www.postgresql.org/docs/current/
|
|
functions-range.html#RANGE-OPERATORS-TABLE>`_). This class is meant as a
|
|
convenient method to avoid typos. The operator names overlap with the names of
|
|
corresponding lookups.
|
|
|
|
.. code-block:: python
|
|
|
|
class RangeOperators:
|
|
EQUAL = "="
|
|
NOT_EQUAL = "<>"
|
|
CONTAINS = "@>"
|
|
CONTAINED_BY = "<@"
|
|
OVERLAPS = "&&"
|
|
FULLY_LT = "<<"
|
|
FULLY_GT = ">>"
|
|
NOT_LT = "&>"
|
|
NOT_GT = "&<"
|
|
ADJACENT_TO = "-|-"
|
|
|
|
RangeBoundary() expressions
|
|
---------------------------
|
|
|
|
.. class:: RangeBoundary(inclusive_lower=True, inclusive_upper=False)
|
|
|
|
.. attribute:: inclusive_lower
|
|
|
|
If ``True`` (default), the lower bound is inclusive ``'['``, otherwise
|
|
it's exclusive ``'('``.
|
|
|
|
.. attribute:: inclusive_upper
|
|
|
|
If ``False`` (default), the upper bound is exclusive ``')'``, otherwise
|
|
it's inclusive ``']'``.
|
|
|
|
A ``RangeBoundary()`` expression represents the range boundaries. It can be
|
|
used with a custom range functions that expected boundaries, for example to
|
|
define :class:`~django.contrib.postgres.constraints.ExclusionConstraint`. See
|
|
`the PostgreSQL documentation for the full details <https://www.postgresql.org/
|
|
docs/current/rangetypes.html#RANGETYPES-INCLUSIVITY>`_.
|
|
|
|
.. _different bounds: https://www.postgresql.org/docs/current/rangetypes.html#RANGETYPES-IO
|